Bibliographic record
Abstract
This book is about the two most fundamental questions underlying current debate about suicide, assisted suicide, and requested euthanasia in medical contexts. Those questions are whether choosing to die rather than endure hopeless torment can be rational , and, if so, whether it is morally permissible . Only if choosing to die is rational and morally permissible can we go on to consider whether provision of assistance in suicide or of euthanasia should be legalized and allowed by codes of medical ethics. The questions are hugely complex and cannot be asked without provision of criterial contexts within which they can be answered. If it is rational to choose to die, it is so within philosophical or conceptual parameters. If it is morally permissible to choose to die, it is so within either universal or culturally determined parameters. Moreover, because most cases of choosing to die occur in institutions like hospitals and hospices, institutional cultures — the policies, priorities, and practices of the relevant institutions — need to be considered in establishing the latter parameters. My original concern with choosing to die or what I call elective death was purely philosophical: I focused on whether choosing to die can be rational ; that is, whether it can accord with reason and be judged to be for the best. At the time I felt that if my work was applicable in actual dealings with individuals prepared to die rather than face personal and physical devastation, that was all to the good, but that was not my main concern.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.077 | 0.037 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".